Distributed optimization based on improved push-sum framework for optimization problem with multiple local constraints and its application in smart grid

Qian XU; Chutian YU; Xiang YUAN; Mengli WEI; Hongzhe LIU

doi:10.1631/FITEE.2200596

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Distributed optimization based on improved push-sum framework for optimization problem with multiple local constraints and its application in smart grid

Special Feature on Intelligent Dynamics Optimization Methods and Their Applications | Updated：2023-09-21

- Distributed optimization based on improved push-sum framework for optimization problem with multiple local constraints and its application in smart grid
- 带多局部约束的改进push-sum框架分布式优化及其在智能电网中的应用
- Frontiers of Information Technology & Electronic Engineering Vol. 24, Issue 9, Pages: 1253-1260(2023)
- Affiliations：
  
  1.State Grid Zhejiang Economic Research Institute, Hangzhou 310008, China
  2.Beijing Yinshan Technology Co., Ltd., Beijing 100871, China
- Author bio：
  
  E-mail: xuqianhangzhou@163.com
  yuchutianhangzhou@163.com
  yuanxianghangzhou@163.com
  wengli33wei@gmail.com
  ‡Corresponding author
- Funds：
- DOI：10.1631/FITEE.2200596
  CLC： O224
- Received：25 November 2022，
  
  Accepted：02 February 2023，
  
  Published Online：28 July 2023，
  
  Published：0 September 2023
- Accepted：
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Qian XU, Chutian YU, Xiang YUAN, et al. Distributed optimization based on improved push-sum framework for optimization problem with multiple local constraints and its application in smart grid[J]. Frontiers of Information Technology & Electronic Engineering, 2023, 24(9): 1253-1260.
DOI：

Qian XU, Chutian YU, Xiang YUAN, et al. Distributed optimization based on improved push-sum framework for optimization problem with multiple local constraints and its application in smart grid[J]. Frontiers of Information Technology & Electronic Engineering, 2023, 24(9): 1253-1260. DOI： 10.1631/FITEE.2200596.

摘要

本文研究了带

个非一致闭凸集约束的分布式优化问题，目的是在固定的不平衡图上设计一个相应的分布式优化算法解决该问题。为此，在改进的push-sum框架下，本文设计了新的分布式优化算法，并在强连通图的假设下给出了其严格的收敛分析。最后，仿真结果证明了所提算法的良好性能。

Abstract

In this paper

the optimization problem subject to

nonidentical closed convex set constraints is studied. The aim is to design a corresponding distributed optimization algorithm over the fixed unbalanced graph to solve the considered problem. To this end

with the push-sum framework improved

the distributed optimization algorithm is newly designed

and its strict convergence analysis is given under the assumption that the involved graph is strongly connected. Finally

simulation results support the good performance of the proposed algorithm.

关键词

Keywords

references

Gharesifard B , Cortés J , 2014 . Distributed continuous-time convex optimization on weight-balanced digraphs . IEEE Trans Autom Contr , 59 （ 3 ）: 781 - 786 . doi: 10.1109/TAC.2013.2278132 http://doi.org/10.1109/TAC.2013.2278132

Kia SS , Cortés J , Martínez S , 2015 . Distributed convex optimization via continuous-time coordination algorithms with discrete-time communication . Automatica , 55 : 254 - 264 . doi: 10.1016/j.automatica.2015.03.001 http://doi.org/10.1016/j.automatica.2015.03.001

Liu HZ , Zheng WX , Yu W , 2021 . Distributed discrete-time algorithms for convex optimization with general local constraints on weight-unbalanced digraph . IEEE Trans Contr Netw Syst , 8 （ 1 ）: 51 - 64 . doi: 10.1109/TCNS.2020.3029996 http://doi.org/10.1109/TCNS.2020.3029996

Liu QS , Wang J , 2015 . A second-order multi-agent network for bound-constrained distributed optimization . IEEE Trans Autom Contr , 60 （ 12 ）: 3310 - 3315 . doi: 10.1109/TAC.2015.2416927 http://doi.org/10.1109/TAC.2015.2416927

Mai VS , Abed EH , 2019 . Distributed optimization over directed graphs with row stochasticity and constraint regularity . Automatica , 102 : 94 - 104 . doi: 10.1016/j.automatica.2018.07.020 http://doi.org/10.1016/j.automatica.2018.07.020

Nedić A , Ozdaglar A , 2009 . Distributed subgradient methods for multi-agent optimization . IEEE Trans Autom Contr , 54 （ 1 ）: 48 - 61 . doi: 10.1109/TAC.2008.2009515 http://doi.org/10.1109/TAC.2008.2009515

Nedić A , Olshevsky A , 2015 . Distributed optimization over time-varying directed graphs . IEEE Trans Autom Contr , 60 （ 3 ）: 601 - 615 . doi: 10.1109/TAC.2014.2364096 http://doi.org/10.1109/TAC.2014.2364096

Nedić A , Ozdaglar A , Parrilo PA , 2010 . Constrained consensus and optimization in multi-agent networks . IEEE Trans Autom Contr , 55 （ 4 ）: 922 - 938 . doi: 10.1109/TAC.2010.2041686 http://doi.org/10.1109/TAC.2010.2041686

Pu S , Shi W , Xu JM , et al. , 2018 . A push-pull gradient method for distributed optimization in networks . IEEE Conf on Decision and Control , p. 3385 - 3390 . doi: 10.1109/CDC.2018.8619047 http://doi.org/10.1109/CDC.2018.8619047

Pu S , Shi W , Xu J , et al. , 2021 . Push pull gradient methods for distributed optimization in networks . IEEE Trans Autom Contr , 66 （ 1 ）: 1 - 16 . doi: 10.1109/TAC.2020.2972824 http://doi.org/10.1109/TAC.2020.2972824

Qu GN , Li N , 2018 . Harnessing smoothness to accelerate distributed optimization . IEEE Trans Contr Netw Syst , 5 （ 3 ）: 1245 - 1260 . doi: 10.1109/TCNS.2017.2698261 http://doi.org/10.1109/TCNS.2017.2698261

Wang J , Elia N , 2011 . A control perspective for centralized and distributed convex optimization . Proc 50 th IEEE Conf on Decision and Control and European Control Conf , p. 3800 - 3805 . doi: 10.1109/CDC.2011.6161503 http://doi.org/10.1109/CDC.2011.6161503

Xi CG , Xin R , Khan UA , 2018 . ADD-OPT: accelerated distributed directed optimization . IEEE Trans Autom Contr , 63 （ 5 ）: 1329 - 1339 . doi: 10.1109/TAC.2017.2737582 http://doi.org/10.1109/TAC.2017.2737582

Yang SF , Liu QS , Wang J , 2017 . A multi-agent system with a proportional-integral protocol for distributed constrained optimization . IEEE Trans Autom Contr , 62 （ 7 ）: 3461 - 3467 . doi: 10.1109/TAC.2016.2610945 http://doi.org/10.1109/TAC.2016.2610945

Yu WW , Liu HZ , Zheng WX , et al. , 2021 . Distributed discrete-time convex optimization with nonidentical local constraints over time-varying unbalanced directed graphs . Automatica , 134 : 109899 . doi: 10.1016/j.automatica.2021.109899 http://doi.org/10.1016/j.automatica.2021.109899

Yuan DM , Xu SY , Zhao HY , 2011 . Distributed primal-dual subgradient method for multiagent optimization via consensus algorithms . IEEE Trans Syst Man Cybern Part B Cybern , 41 （ 6 ）: 1715 - 1724 . doi: 10.1109/TSMCB.2011.2160394 http://doi.org/10.1109/TSMCB.2011.2160394

Zhu MH , Martínez S , 2012 . On distributed convex optimization under inequality and equality constraints . IEEE Trans Autom Contr , 57 （ 1 ）: 151 - 164 . doi: 10.1109/TAC.2011.2167817 http://doi.org/10.1109/TAC.2011.2167817

Zhu YN , Yu WW , Wen GH , et al. , 2019a . Continuous-time coordination algorithm for distributed convex optimization over weight–unbalanced directed networks . IEEE Trans Circ Syst II Express Briefs , 66 （ 7 ）: 1202 - 1206 . doi: 10.1109/TCSII.2018.2878250 http://doi.org/10.1109/TCSII.2018.2878250

Zhu YN , Yu WW , Wen GH , et al. , 2019b . Continuous-time distributed subgradient algorithm for convex optimization with general constraints . IEEE Trans Autom Contr , 64 （ 4 ）: 1694 - 1701 . doi: 10.1109/TAC.2018.2852602 http://doi.org/10.1109/TAC.2018.2852602

Zimmermann J , Tatarenko T , Willert V , et al. , 2020 . Projected push-sum gradient descent-ascent for convex optimization with application to economic dispatch problems . Proc 59 th IEEE Conf on Decision and Control , p. 542 - 547 . doi: 10.1109/CDC42340.2020.9304360 http://doi.org/10.1109/CDC42340.2020.9304360

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